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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Apr 6, 2026
Date Accepted: Sep 17, 2026

The final, peer-reviewed published version of this preprint can be found here:

Conditions and Pathways for Integrating Smart Care Robots Into Long-Term Care Facilities: Qualitative Study From Nursing Assistants’ Perspectives

An Y, Zhang F, Yang Y, Martin-Payo R, Xie X

Conditions and Pathways for Integrating Smart Care Robots Into Long-Term Care Facilities: Qualitative Study From Nursing Assistants’ Perspectives

J Med Internet Res 2026;28:e97371

DOI: 10.2196/97371

Conditions and Pathways for Integrating Smart Care Robots into Long-Term Care Facilities: A Qualitative Study from Nursing Assistants’ Perspectives

  • Yawen An; 
  • Fengying Zhang; 
  • Yang Yang; 
  • Ruben Martin-Payo; 
  • Xiaofeng Xie

ABSTRACT

Background:

Smart care robots are increasingly viewed as a potential way to address care burden and support care quality in long-term care facilities. However, their integration into routine care practice remains limited, and the conditions required for their effective implementation are not yet well understood from the perspective of frontline nursing assistants.

Objective:

To clarify nursing assistants’ core functional expectations of smart care robots in long-term care facilities and to explore the key conditions for their integration into practice.

Methods:

A descriptive qualitative study was conducted. Using purposive sampling, frontline nursing assistants were recruited from five long-term care facilities in Sichuan Province, China, with recruitment assistance from facility administrators and eligibility screening by the research team. Semi-structured face-to-face interviews were conducted with 31 nursing assistants between September and November 2025. The data were analysed using thematic analysis

Results:

Four themes were identified: real-world care needs, limited facilitating conditions, major barriers, and preparatory pathways for implementation. Participants expected robots to support safety monitoring and risk warning, standardized checking and management, repetitive physical tasks, and basic interaction. Although some openness to technology and organizational support existed, these facilitating conditions were insufficient for routine implementation. Key barriers included unclear human–robot collaboration models, inadequate organizational capacity, potential new care risks, and weak external support. Participants emphasized organizational assessment, contextual adaptation, pilot testing, and structured training as essential preparatory steps. Emotional support functions were also valued for alleviating caregivers’ emotional burden in high-intensity care work.

Conclusions:

The integration of smart care robots into long-term care facilities is not merely a matter of technology adoption, but a process that requires alignment across technology, organisations, users, and care recipients.


 Citation

Please cite as:

An Y, Zhang F, Yang Y, Martin-Payo R, Xie X

Conditions and Pathways for Integrating Smart Care Robots Into Long-Term Care Facilities: Qualitative Study From Nursing Assistants’ Perspectives

J Med Internet Res 2026;28:e97371

DOI: 10.2196/97371

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